
Environmental Data Science
@EnvDataScience
Environmental Data Science is an #OpenAccess @CambridgeUP journal dedicated to the use of data science & AI to enhance our understanding of the environment.
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📢 CALL FOR PAPERS REMINDER! Connecting #Data-Driven and #Physical Approaches: Application to #Climate #Modeling and #EarthSystem Observation 🗓️ 31st Oct 2025 ℹ️ bit.ly/4k09cBu Consider submitting your work! @brajard #EGU2025

📢 CALL FOR PAPERS: Connecting Data-Driven and Physical Approaches: Application to Climate Modeling and Earth System Observation Only 1 month left to submit to this special collection building upon a workshop at #EGU25. ℹ️ bit.ly/4k09cBu @brajard #climate #AI

Recently published! Precipitation prediction over the upper Indus Basin from large-scale circulation patterns using Gaussian processes 👉 bit.ly/4nojwoo ✍️ @KenzaxTazi, Andrew Orr, J. Scott Hosking & Richard E. Turner (@BAS_News, @Cambridge_Uni, @turinginst)

New article! Toward accurate forecasting of renewable energy: Building datasets and benchmarking machine learning models for solar and wind power in France 👉 bit.ly/4mCtrWj ✍️ Eloi Lindas, @YannigGoude & @ciais_philippe @LSCE_IPSL #climate #MachineLearning

New article! Air quality prediction from images in Indonesia: enhancing model explainability through visual explanation with AQI-net and grad-CAM 👉 bit.ly/4g434qD ✍️ Muhammad Labib Alauddin, Novanto Yudistira & Muhammad Arif Rahman @Climformatics #CI2025 #airquality

Recently published! 🌍 Crafting desirable climate trajectories with reinforcement learning explored socio-environmental simulations 👉 bit.ly/4oVbLre ✍️James Rudd-Jones, Fiona Thendean & @MPerezOrtiz_ (@ai_ucl, @uclcs) #ClimateChange #ClimatePolicy

New article! 🌍🛰️ Discrete variational autoencoders for synthetic nighttime visible satellite imagery 👉 bit.ly/4oVjTb5 ✍️ Mickell D. Als, David Tomarov & Steve Easterbrook (@UofTCompSci) Part of the @Climformatics #CI2025 collection #DeepLearning #RemoteSensing

New article!🌍💨💡 Turbine location-aware multi-decadal wind power predictions for Germany using CMIP6 👉 doi.org/10.1017/eds.20… ✍️ Nina Effenberger & Nicole Ludwig (@uni_tue) #ClimateChange #WindPower #Energy
New article! 🌳🌍 Tree semantic segmentation from aerial image time series 👉doi.org/10.1017/eds.20… ✍️Venkatesh Ramesh @ArthurOuaknine @david_rolnick Research that advances #forest monitoring using #deeplearning on aerial imagery time series.

MoTiF: a self-supervised model for multi-source #forecasting with application to #tropical #cyclones 🌀🌍 ✍️Clément Dauvilliers & Claire Monteleoni (@inria_paris & @CUBoulder) 👉doi.org/10.1017/eds.20… Presents a new #deeplearning #AI method for forecasting #extremeweather.

In honour of the 31st ACM/SIGKDD Knowledge and Data Discovery Conference this week, enjoy free access to our curated article collection - featuring content from @EnvDataScience, @Data_and_Policy, @DCE_Journal and @nws_journal. Explore the full collection: cup.org/4fm0dce

📢 CALL FOR PAPERS: Connecting Data-Driven and Physical Approaches: Application to Climate Modeling and Earth System Observation This special collection will build upon a workshop at #EGU25. 🗓️31st Oct 2025 ℹ️bit.ly/4k09cBu @brajard #climate #AI #forecasting

Discover Environmental Data Science, an #OpenAccess journal focused on #data-driven methods for studying #environmental processes like #climatechange & supporting sustainable decision-making. Check out our 2024 metrics and learn more at: bit.ly/47aNIht #datascience
Position paper published! Opportunities and challenges of quantum computing for climate modeling 👉 bit.ly/4591Cyb Mierk Schwabe, Lorenzo Pastori, Inés de Vega, @PierreGentine, Luigi Iapichino, Valtteri Lahtinen, Martin Leib, Jeanette Miriam Lorenz & Veronika Eyring

New article! Development of a comprehensive bilateral trade-flow dataset of the environmental pressures of global food production 👉 bit.ly/3TPYC4q By authors from @ucsantabarbara, @LancasterUni, @UTAS_, @UW & @UniversityLeeds #climatechange #agriculture #food

New article! Uncertainty bounds for long-term causal effects of perturbations in spatiotemporal systems 👉 bit.ly/3Idjb8x By @KDebeire, Andreas Gerhardus, Renée Bichler, @runge_jakob & Veronika Eyring #spatiotemporalmodels #uncertaintyestimations

Introducing our new Editor @PMoutis! Welcome to our board! We have assembled an international advisory board of experts in the field of environmental data science. View our board here: cambridge.org/core/journals/… #environment #data #climatechange

New article! Classification-informed estimation: the role of water-type clustering to improve neural network generalization for salinity and temperature estimation in coastal waters 👉 bit.ly/4kRZfG7 By authors from @EdinburghUni, @CefasGovUK, @StirUni & @NOCnews

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